Pylearn2 yaml_parse.load code injection

CVSS Meta Temp Score
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Current Exploit Price (≈)
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CTI Interest Score
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8.5$0-$5k0.00

Summaryinfo

A vulnerability identified as critical has been detected in Pylearn2. Impacted is the function yaml_parse.load. Performing a manipulation results in code injection. This vulnerability is reported as CVE-2018-20027. The attack is possible to be carried out remotely. No exploit exists.

Detailsinfo

A vulnerability was found in Pylearn2 (affected version not known). It has been classified as critical. This affects the function yaml_parse.load. The manipulation with an unknown input leads to a code injection vulnerability. CWE is classifying the issue as CWE-94. The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

The yaml_parse.load method in Pylearn2 allows code injection.

The bug was discovered 12/11/2018. The weakness was disclosed 12/17/2018 (Website). It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2018-20027 since 12/10/2018. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. Technical details of the vulnerability are known, but there is no available exploit. The attack technique deployed by this issue is T1059 according to MITRE ATT&CK.

The vulnerability was handled as a non-public zero-day exploit for at least 6 days. During that time the estimated underground price was around $0-$5k.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Name

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 8.5
VulDB Meta Temp Score: 8.5

VulDB Base Score: 7.3
VulDB Temp Score: 7.3
VulDB Vector: 🔍
VulDB Reliability: 🔍

NVD Base Score: 9.8
NVD Vector: 🔍

CVSSv2info

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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍

NVD Base Score: 🔍

Exploitinginfo

Class: Code injection
CWE: CWE-94 / CWE-74 / CWE-707
CAPEC: 🔍
ATT&CK: 🔍

Physical: No
Local: No
Remote: Yes

Availability: 🔍
Status: Not defined

EPSS Score: 🔍
EPSS Percentile: 🔍

Price Prediction: 🔍
Current Price Estimation: 🔍

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔍

Timelineinfo

12/10/2018 🔍
12/11/2018 +1 days 🔍
12/17/2018 +6 days 🔍
12/17/2018 +0 days 🔍
12/18/2018 +1 days 🔍
06/19/2023 +1644 days 🔍

Sourcesinfo

Advisory: 1593
Status: Not defined

CVE: CVE-2018-20027 (🔍)
GCVE (CVE): GCVE-0-2018-20027
GCVE (VulDB): GCVE-100-128067

Entryinfo

Created: 12/18/2018 09:21
Updated: 06/19/2023 16:23
Changes: 12/18/2018 09:21 (54), 04/21/2020 16:42 (1), 06/19/2023 16:23 (3)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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